Demo Data from EDBT 2026 / reviewers in the wild / expert
Garret A. FitzGerald
dblp:26/7066
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 50% Computational science and engineering · 50% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 50% Image and video processing · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
circadian rhythm analysis |
0.1 | 1 | 2008 | WAVECLOCK: wavelet analysis of circadian oscillation · Bioinform. 2008 |
Computational science and engineering › dynamical systems
oscillator analysis |
0.1 | 1 | 2008 | WAVECLOCK: wavelet analysis of circadian oscillation · Bioinform. 2008 |
Audio and music processing
time-frequency analysis |
0.1 | 1 | 2008 | WAVECLOCK: wavelet analysis of circadian oscillation · Bioinform. 2008 |
Image and video processing › wavelet transform
wavelet decomposition |
0.1 | 1 | 2008 | WAVECLOCK: wavelet analysis of circadian oscillation · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
non-parametric modeling · 0.2continuous wavelet transform · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | WAVECLOCK: wavelet analysis of circadian oscillationabstractUNLABELLED: Oscillations in mRNA and protein of circadian clock components can be continuously monitored in vitro using synchronized cell lines. These rhythms can be highly variable due to culture conditions and are non-stationary due to baseline trends, damping and drift in period length. We present a technique for characterizing the modal frequencies of oscillation using continuous wavelet decomposition to non-parametrically model changes in amplitude and period while removing baseline effects and noise. AVAILABILITY: The method has been implemented as the package waveclock for the free statistical software program R and is available for download from http://cran.r-project.org/ Thomas S. Price, Julie E. Baggs, Anne M. Curtis, Garret A. FitzGerald, John B. Hogenesch |
Bioinform. | 4 |